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面向智能电网嵌入式设备的网络威胁动态评估方法
引用本文:吕卓,郭志民,陈岑,莫坚松,常朝稳.面向智能电网嵌入式设备的网络威胁动态评估方法[J].北京航空航天大学学报,2022,48(2):324-330.
作者姓名:吕卓  郭志民  陈岑  莫坚松  常朝稳
作者单位:1.国网河南省电力公司电力科学研究院, 郑州 450052
基金项目:国家自然科学基金(U1736114)~~;
摘    要:针对智能电网嵌入式设备由于计算、存储资源有限而造成的对网络攻击行为应对不足,安全评估手段薄弱等问题,提出了面向智能电网嵌入式设备的网络攻击行为动态评估方法。使用安全控制模块对实际嵌入式设备通信数据流进行解析与判别,利用组件动态可信度量分析方法在嵌入式系统模拟机中对攻击行为安全影响进行安全检测评估,通过对平台配置属性、平台运行属性及用户认证属性3个方面属性进行全过程动态综合度量,得出最终网络攻击行为安全评估结果。通过在配电自动化及用电信息采集系统真实环境下进行测试,针对嵌入式设备常见的攻击行为,检测方法的准确率能够达到90%以上,具备较好的安全评估精度,与此同时实现了自身安全性的有效提升。 

关 键 词:动态评估    属性度量    安全检测    网络攻击行为    动态可信度量
收稿时间:2020-08-09

A dynamic network threat evaluation method for smart grid embedded devices
LYU Zhuo,GUO Zhimin,CHEN Cen,MO Jiansong,CHANG Chaowen.A dynamic network threat evaluation method for smart grid embedded devices[J].Journal of Beijing University of Aeronautics and Astronautics,2022,48(2):324-330.
Authors:LYU Zhuo  GUO Zhimin  CHEN Cen  MO Jiansong  CHANG Chaowen
Institution:1.State Grid Henan Electric Power Research Institute, Zhengzhou 4500522.Information Engineering University of PLA Strategic Support Force, Zhengzhou 450004, China
Abstract:Due to the limited computing and storage resources, the smart grid embedded devices cannot deal with the network attacks effectively and the security assessment method is weak. In order to solve these problems, a dynamic network attack behavior evaluation method for smart grid embedded devices is proposed. This method uses the security control module to analyze the communication data stream of the actual embedded device, and conduct security detection evaluation of the impact of the attack behavior in the embedded system simulator by using the component dynamic trust measurement. The final security evaluation result of the network attacks is obtained based on the whole process dynamic comprehensive measurement of the platform configuration property, the platform operation attribute and the user authentication attribute. The method is tested in the actual environment of the power distribution automation system and the power utilization information collection system. The results show that, aimed at the common attacks against the embedded devices, accuracy rate of the proposed detection method can reach more than 90%. This method provides good safety assessment accuracy, and meanwhile achieves effective upgrade of its own security. 
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